Parallel FindAll integration

import getpass
import os

if not os.environ.get("PARALLEL_API_KEY"):
    os.environ["PARALLEL_API_KEY"] = getpass.getpass("Parallel API key:\n")

from langchain_parallel import ParallelFindAllTool

tool = ParallelFindAllTool(generator="preview")

from langchain_parallel import FindAllMatchCondition

result = await tool.ainvoke({
    "objective": "Pure-play public LLM API providers",
    "entity_type": "company",
    "match_conditions": [
        FindAllMatchCondition(
            name="public_us",
            description="Company is publicly traded on a US exchange",
        ),
        FindAllMatchCondition(
            name="llm_api_revenue",
            description="Primary revenue is selling LLM inference via API",
        ),
    ],
    "match_limit": 5,
})

for c in result["candidates"]:
    print(c["name"], "—", c["url"])

Anthropic — https://www.anthropic.com
OpenAI — https://www.openai.com
...

deep = ParallelFindAllTool(generator="core")

result = await deep.ainvoke({
    "objective": "Independent solar-installer companies based in the EU",
    "entity_type": "company",
    "match_conditions": [
        FindAllMatchCondition(
            name="eu_hq",
            description="Headquartered in an EU country",
        ),
        FindAllMatchCondition(
            name="residential_solar_pv",
            description="Primarily installs residential solar PV",
        ),
    ],
    "match_limit": 50,
})

from langchain_parallel import FindAllExcludeEntry

result = await tool.ainvoke({
    "objective": "Pure-play public LLM API providers",
    "entity_type": "company",
    "match_conditions": [
        FindAllMatchCondition(
            name="llm_api_revenue",
            description="Primary revenue is selling LLM inference via API",
        ),
    ],
    "match_limit": 5,
    "exclude_list": [
        FindAllExcludeEntry(name="OpenAI", url="https://www.openai.com"),
        FindAllExcludeEntry(name="Anthropic", url="https://www.anthropic.com"),
    ],
})

# from another task / handler:
tool.cancel(findall_id)        # sync
await tool.acancel(findall_id) # async

from langchain.agents import create_agent
from langchain.chat_models import init_chat_model

llm = init_chat_model(model="claude-haiku-4-5", model_provider="anthropic")
agent = create_agent(model=llm, tools=[tool])

agent.invoke({"messages": [("human", "Find me a few independent EU solar installers.")]})

{
    "candidates": [
        {
            "candidate_id": "cand_abc",
            "name": "Acme Solar",
            "url": "https://acmesolar.example",
            "description": "...",
            "match_status": "matched",  # or "generated" / "unmatched"
            "output": {
                "<condition_name>": {
                    "type": "match_condition",
                    "value": True,
                    "is_matched": True,
                },
            },
            "basis": [...],  # citations + reasoning per output field
        },
    ],
    "run": {...},          # status info
    "last_event_id": "...",
}